The present application describes systems and techniques relating to monitoring physiological activity of an organism, for example, performing QRS detection on a cardiac signal obtained from a person.
The electrical activity of various organs, such as the heart or brain, can be monitored, and this electrical activity can be analyzed to look for patterns that may assist in diagnosing various conditions. For example, the electrical activity of the heart can be monitored to track various aspects of the functioning of the heart. Given the volume conductivity of the body, electrodes on the body surface or beneath the skin can display potential differences related to this activity. Anomalous electrical activity can be indicative of disease states or other physiological conditions ranging from benign to fatal.
Cardiac monitoring devices can sense the cardiac electrical activity of a living being and identify heart beats. Frequently, identification of heart beats is performed by identifying the R waves in the QRS complex, as can be seen in an electrocardiogram (ECG). The R wave represents ventricular depolarization. The typically large amplitude of this wave in the QRS complex is useful in identifying a heart beat. Traditional automated ECG signal analysis tools typically rely on correlation-based template matching and a number of empirical decision rules that are optimized for certain ECG databases. Many techniques have been developed for performing QRS detection, but further improvements are desirable.